Introduces the first benchmark for multicultural text-to-image generation across five countries and a MosAIG multi-agent framework, showing that richer prompts improve quality but disparities persist across languages and demographics.
In Proceedings of the IEEE/CVF International Confer- ence on Computer Vision, pages 20406–20417
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A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
citing papers explorer
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When Cultures Meet: Multicultural Text-to-Image Generation
Introduces the first benchmark for multicultural text-to-image generation across five countries and a MosAIG multi-agent framework, showing that richer prompts improve quality but disparities persist across languages and demographics.
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Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global South
A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.